eo-tides 0.0.20

Tide modelling tools for large-scale satellite earth observation analysis

eo-tides: Tide modelling tools for large-scale satellite earth observation analysis

• Github repository: https://github.com/GeoscienceAustralia/eo-tides/
• Documentation https://GeoscienceAustralia.github.io/eo-tides/

[!CAUTION] This package is a work in progress, and not currently ready for operational use.

The eo-tides package provides powerful, parallelized tools for seamlessly integrating satellite Earth observation data with tide modelling.

eo-tides combines advanced tide modelling functionality from the pyTMD package and integrates it with pandas, xarray and odc-geo, providing a suite of flexible tools for efficient analysis of coastal and ocean earth observation data – from regional, continental, to global scale.

These tools can be applied to petabytes of freely available satellite data (e.g. from Digital Earth Australia or Microsoft Planetary Computer) loaded via Open Data Cube's odc-stac or datacube packages, supporting coastal and ocean earth observation analysis for any time period or location globally.

Highlights

• 🌊 Model tides from multiple global ocean tide models in parallel, and return tide heights in standardised pandas.DataFrame format for further analysis
• 🛰️ "Tag" satellite data with tide height and stage based on the exact moment of image acquisition
• 🌐 Model tides for every individual satellite pixel, producing three-dimensional "tide height" xarray-format datacubes that can be combined with satellite data
• 🎯 Combine multiple tide models into a single locally-optimised "ensemble" model informed by satellite altimetry and satellite-observed patterns of tidal inundation
• 📈 Calculate statistics describing local tide dynamics, as well as biases caused by interactions between tidal processes and satellite orbits
• 🛠️ Validate modelled tides using measured sea levels from coastal tide gauges (e.g. GESLA Global Extreme Sea Level Analysis)

Supported tide models

eo-tides supports all ocean tide models supported by pyTMD. These include:

• Empirical Ocean Tide model (EOT20)
• Finite Element Solution tide models (FES2022, FES2014, FES2012)
• TOPEX/POSEIDON global tide models (TPXO10, TPXO9, TPXO8)
• Global Ocean Tide models (GOT5.6, GOT5.5, GOT4.10, GOT4.8, GOT4.7)
• Hamburg direct data Assimilation Methods for Tides models (HAMTIDE11)

For instructions on how to set up these models for use in eo-tides, refer to Setting up tide models.

Citing eo-tides

To cite eo-tides in your work, please use the following citation:

Bishop-Taylor, R., Sagar, S., Phillips, C., & Newey, V. (2024). eo-tides: Tide modelling tools for large-scale satellite earth observation analysis [Computer software]. https://github.com/GeoscienceAustralia/eo-tides